In cloud computing, there are many strategies used for virtual machine (VM) placement. Objectives for VM placement are to reduce the number of physical machines required, VM allocation time and to reduce resource and power wastage. Various VM placement algorithms and the problems of existing techniques are analyzed and discussed here. The evaluation of those algorithms is given with the factors...

Cloud computing and Network Function Virtualization (NFV) use cases proposed by ETSI can improve network caching when an adequate optimization algorithm is used. A cache placement algorithm is proposed based on these virtualization tools. Moreover, a cache placement protocol is presented to support the cache migration. Optimal cache and Virtual Machine (VM) placement and migration, and optimal ...

We present an approach to optimal virtual machine placement within datacenters for predicable and time-constrained load peaks. A method for optimal load balancing is developed, based on binary integer programming. For tradeoffs between quality of solution and computation time, we also introduce methods to pre-process the optimization problem before solving it. Upper bound based optimizations ar...

Due to the high availability of resources in the Cloud Computing platform, there is a tremendous increase in the underutilization of these resources. Improving the throughput and effectively utilizing these resources are two main challenges in the cloud computing scenario. This paper proposes a methodology for improving the throughput and effective utilization of resources by appropriately plac...

Finding the best way to map virtual machines (VMs) to physical machines (PMs) in a cloud data center is an important optimization problem, with significant impact on profitability, performance, and energy consumption. In most situations, the computational capacity of PMs and the computational load of VMs are a vital aspect to consider in the VM-to-PM mapping. Previous work modeled computational...

Cloud service providers operate multiple geographically distributed data centers. These data centers consume huge amounts of energy, which translate into high operating costs. Interestingly, the geographical distribution of the data centers provides many opportunities for cost savings. For example, the electricity prices and outside temperatures may be widely different at the data centers. This...

Cloud computing datacenters provide millions of virtual machines in actual cloud markets. In this context, Virtual Machine Placement (VMP) is one of the most challenging problems in cloud infrastructure management, considering the large number of possible optimization criteria and different formulations that could be studied. Considering the on-demand model of cloud computing, the VMP problem s...

Energy consumption of data centers increased continously during the last decades. As current techniques for improving their energy efficiency are usually limited to one type of data center components, it is difficult to employ them for a holistic optimization which may utilize synergies between all components. This paper introduces architecture and working principles of the novel energy managem...

Resource allocation strategies in virtualized data centers have received considerable attention recently as they can have substantial impact on the energy efficiency of a data center. This led to new decision and control strategies with significant managerial impact for IT service providers. We focus on dynamic environments where virtual machines need been analyzed and used to place virtual mac...